We turn manual processes and scattered knowledge into automations, agents, and AI products your team can use — and measure.
30 minutes · No commitment · Leave with one priority opportunity identifiedWe talk efficiency with Operations, adoption with Product, and integration with Technology.
Clear scope, clear decision. Each format reduces a different kind of risk.
A paid diagnosis that turns scattered ideas into one prioritized, costed opportunity.
Validate an automation or agent with real users and day-to-day data.
Launch an AI feature, copilot, or product with continuous improvement.
Before we promise results, we ship software. These products were designed, built, and are operated by the AI Factory team.
Agents that run growth workflows end to end — content, outreach, and follow-up.
An agent that answers, qualifies, and routes customer conversations.
Operations platform for vehicle fleets — tracking, maintenance, and cost control.
Extracts data from invoices and turns it into structured, system-ready records.
Each product is a live testbed for the same Factory method we apply to client work — ask for a demo in the diagnostic.
How we design an automation pilot without hiding risk, integration, or human involvement.
Emails arrive in different formats; the team reads, classifies, searches for information, and updates systems.
The agent extracts data, checks authorized sources, and routes exceptions for human validation.
Permissions, logs, and integrations are defined with the technical team before the pilot.
We compare the process before and after; we only scale when the evidence supports it.
I want to design a similar case →From the first workflow to a production product, every capability starts with a concrete problem.
Assistants with context, tools, and permissions to execute tasks.
We connect email, CRM, ERP, and APIs to reduce manual steps.
Intelligent search and RAG across internal sources, with traceability.
Copilots, recommendations, and generative experiences in your software.
We map the process, volume, data, exceptions, and success metric.
A working version in the team’s hands to measure usefulness, quality, and risk.
We integrate systems, define controls, and prepare monitoring.
We monitor usage, costs, and drift to evolve with the business.
The technical design is tailored to risk and client policies, with explicit decisions.
Every solution runs where it makes sense — cloud, hybrid, or fully on your own infrastructure.
Best for most workloads — elastic capacity, zero hardware to manage.
Sensitive data stays local; heavier models run in the cloud.
Everything on your hardware — local models, no token billing, no data leaving the building. Gen 1 launch: Portugal only.
See the appliances →Every case starts with a baseline. These are the three kinds of evidence we bring to the decision.
Task time, cycle time, and manual work avoided.
Errors, corrections, exceptions, and consistency.
Active users, completion, and feedback.
The right questions save weeks of work and prevent false expectations.
The AI Discovery maps processes, data, risk, and impact to choose a concrete opportunity — from €750, credited toward the pilot.
Yes — AVANTO AGP, ROBIN CRA, Fleetos, and E-invoice were built by our team and are running today. Ask for a demo.
Yes. AI Factory Appliances run models locally — no token billing and no data leaving your infrastructure.
Not always. We integrate with what exists when it is safe and sensible, validating feasibility before making promises.
A well-scoped pilot is designed for 4 to 6 weeks. Complex integrations or data preparation may require a different timeline.
Sources, permissions, retention, providers, and human involvement are defined per project and confirmed with the client.
We choose based on quality, cost, latency, and privacy; when it makes sense, we separate business logic from the model.
We agree on a baseline and criteria: time, quality, exceptions, usage, and cost. The outcome is a decision to proceed, adjust, or stop.
In 30 minutes, we identify one priority opportunity and the smallest next step that produces evidence.